Various techniques exist for processing digital video data for purposes of image recognition, pattern recognition, object detection, etc. Typically, video data is captured by one type of device and then analyzed by the device or by another processing device. For example, one method includes acquiring visual image primitives from a video input comprising visual information relevant to a human activity. The primitives are temporally aligned to an optimally hypothesized sequence of primitives transformed from a sequence of transactions as a function of a distance metric between the observed primitive sequence and the transformed primitive sequence. Another method detects a moving target with the use of a reference image and an inspection image from the images captured by one or more cameras. A moving target is detected from the reference image and the inspection image based on the orientation of corresponding portions in the reference image and the inspection image relative to a location of an epipolar direction common to the reference image and the inspection image; and displays any detected moving target on a display.
Current video data processing techniques typically operate on one type of video input data. Making available a larger source of data aggregated from multiple sources into a combined source has not been possible for individual contributors.
In addition, it has proven challenging to process large amounts of streaming video data effectively.
It would be desirable to have a system and method for receiving digital video data from multiple sources of different types and be able to analyze the raw data as a single data source from the different sources to determine facts about a scene both at a point in time and over a period of time.